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Quantum Computers Just Proved The Simulation Theory Is Terrifying

Time is something we experience every day, yet scientists still struggle to fully understand what it really is. Now, advances in quantum computing are allowing researchers to explore some of the deepest mysteries of physics—and the results are raising extraordinary questions about the nature of time itself.

By simulating complex quantum systems that were previously impossible to study, quantum computers are helping scientists test theories about causality, time reversal, and the strange behavior of particles at the quantum level. Some findings appear to challenge our most basic assumptions about how time works.

Researchers are investigating whether time is truly fundamental to the universe or whether it emerges from deeper physical processes we have yet to understand. These ideas may sound like science fiction, but they are being explored by some of the world’s leading physicists.

The implications are profound. If our understanding of time is incomplete, it could affect everything from cosmology and black holes to the future of computing and our understanding of reality itself.

In this video, we examine the groundbreaking quantum experiments, the theories they are testing, and why some scientists believe these discoveries could transform our view of the universe.

Watch until the end to uncover the most mind-bending implications of this research. Don’t forget to LIKE, SHARE, and SUBSCRIBE for more cutting-edge science, quantum mysteries, and incredible discoveries. Comment below: What do you think time really is?

The Simulated Multiverse: An MIT Computer Scientist Explores Parallel Universes, Quantum Computing, The Simulation Hypothesis and the Mandela Effect

Do multiple versions of ourselves exist in parallel universes living out their lives in different timelines?In this follow up to his bestseller, The Simulation Hypothesis, MIT Computer Scientist and Silicon Valley Game Pioneer Rizwan Virk explores these topics from a new that of simulation theory. If we are living in a digital universe, then many of the complexities and baffling characteristics of our reality start to make more sense. Quantum computing lets us simulate complex phenomena in parallel, allowing the simulation to explore many realities at once to find the most “optimum” path forward. Could this explain not only the enigmatic Mandela Effect but provide us with a new understanding of time and space? Bringing his unique trademark style of combining video games, computer science, quantum physics and computing with lots of philosophy and science fiction, Virk gives us a new way to think about not just our universe, but all possible realities!

Show more.

Google Is Mapping the Human Brain… and It Gets Terrifying

Google is using AI to map the human brain, generate synthetic neurons, and speed up one of the most ambitious neuroscience projects ever attempted. But as brain mapping, connectomics, and AI brain decoding move forward, a terrifying question appears: what happens to mental privacy when machines can understand the brain better than we do?

This mini-documentary explores Google’s brain mapping research, synthetic neurons, AI mind decoding, neural privacy, and the future of human thought in the age of artificial intelligence.

CHAPTERS:
00:00 Google’s Brain Mapping Project.
02:00 The Scale of the Human Brain.
04:36 Synthetic Neurons Explained.
06:40 AI Is Already Decoding Thoughts.
10:15 The Rise of Neural Privacy.
14:51 Brain Maps and the Future of AI
17:11 Who Owns Your Mind?

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Welcome to AI Uncovered, your ultimate destination for exploring the fascinating world of artificial intelligence! Our channel delves deep into the latest AI trends and technology, providing insights into cutting-edge AI tools, AI news, and breakthroughs in artificial general intelligence (AGI). We simplify complex concepts, making AI explained in a way that is accessible to everyone.

At AI Uncovered, we’re passionate about uncovering the most captivating stories in AI, including the marvels of ChatGPT and advancements by organizations like OpenAI. Our content spans a wide range of topics, from science news and AI innovations to in-depth discussions on the ethical implications of artificial intelligence. Our mission is to enlighten, inspire, and inform our audience about the rapidly evolving technology landscape.

Google DeepMind AI Discovered a Mathematical Pattern Hidden in Prime Numbers

What exactly did DeepMind find?
Could this discovery help solve longstanding mathematical mysteries?
And what might it mean for cryptography, computing, and our understanding of mathematics itself?

In this video, we explore the science behind the discovery, the role of artificial intelligence in modern research, and why mathematicians around the world are paying close attention.

Whether this breakthrough leads to a revolutionary new theorem or simply a deeper understanding of prime numbers, it demonstrates the growing power of AI to accelerate scientific progress.

👇 What do YOU think?
Will AI help solve the greatest unsolved problems in mathematics?

💬 COMMENT below, 👍 LIKE the video, and 🔔 SUBSCRIBE for more AI breakthroughs, mathematical mysteries, and cutting-edge science discoveries!

Loss of sirtuin 3 disrupts cellular senescence signaling pathways

Cellular senescence is a multifaceted stress response marked by stable proliferative arrest and the secretion of diverse biologically active factors, collectively known as the senescence-associated secretory phenotype (SASP). The senescent phenotype is remarkably variable and subject to various regulatory influences. We previously demonstrated that mitochondrial dysfunction induced by diverse stimuli, including the loss of sirtuin 3 (SIRT3), leads to the hyperactivation of AMPK and p53, culminating in senescence while concurrently suppressing much of the proinflammatory SASP. Here, we extend our findings by revealing that the absence of SIRT3 can suppress segments of the SASP even in the absence of p53. Intriguingly, SIRT3 deficiency renders cells resistant to stimulation by exogenous cytokines, such as interleukin-1.

Stretching the skin can alter how we perceive our fingers

When moving around in their surroundings, humans heavily rely on what is known as proprioception, sometimes referred to as the “sixth sense.” This is the body’s subconscious ability to sense its own position, movements and location in space, via many tiny receptors that respond to mechanical strain located in the muscles, tendons and skin.

Researchers at University of Pisa, the Italian Institute of Technology (IIT), and University of Rome Tor Vergata recently carried out a study investigating how artificially stretching the skin while people are moving their fingers influences proprioception. Their findings, published in the Journal of the Royal Society Interface, suggest that precisely deforming the skin while people are flexing their fingers alters how they perceive their hand and finger postures.

“According to common belief, humans have only five senses: vision, hearing, taste, smell, and touch; yet physiology tells us there are more,” Eleonora Fontana, first author of the paper, told Medical Xpress. “An essential, often overlooked ‘sixth sense’ is proprioception—our body’s ability to perceive limb position and movement in space. While much of this information is processed subconsciously, it is central to guiding our everyday movements; in fact, individuals with proprioceptive deficits suffer from severe movement impairments.”

Understanding and targeting erythroid cell metabolism

Red blood cell (RBC) production, or erythropoiesis, serves as a paradigm for studying cellular differentiation in both physiological and pathological contexts. While the transcriptional and epigenetic programs controlling erythropoiesis are well characterized, the metabolic regulation of this complex process remains underexplored. Recent discoveries that pyruvate kinase activators improve outcomes in sickle cell disease and thalassemia underscore the therapeutic potential of targeting metabolism in RBC disorders. However, further progress is limited by an incomplete understanding of the metabolic networks supporting erythropoiesis and RBC function.

Ken Hayworth: Brain Preservation is the Logical Lifeboat

Thirteen years ago, I sat down with Ken Hayworth and asked him a question most people spend their whole lives avoiding.

What happens to the self when the body fails?

Ken is president of the Brain Preservation Foundation. He is also a neuroscientist who refuses to flinch. His answer was not comfort. It was logic.

Brain preservation, he argued, is the logical lifeboat that people have access to today.

Here is the part that has stayed with me ever since. Ken imagines our grandchildren looking back at us. They will see that we had the science. They will see that we understood the brain holds our memories, our skills, our personality. And they will ask why we did nothing.

His verdict is brutal. We were not killed by bad technology. We were killed by bad philosophy. We simply could not accept that we are physical machines.

From Worm to AI: How Control Theory Unlocks Neural Networks

In this video, Dr. Ardavan (Ahmad) Borzou will discuss the control theory in network science and its application in C. elegans \& artificial neural networks. A short history of network science and the basics of control theory will also be reviewed.

Comprehensive Python Checklist (machine learning and more advanced libraries will be covered on a different page):
https://compu-flair.com/blogs/program… Website: www.compu-flair.com Chapters: 00:00 — Introduction 01:52 — Application of control theory in the neural net of worm 03:23 — Networks in Data Science & Seven Bridges of Konigsberg Problem 05:00 — History of network science 06:22 — Basics of control theory 10:23 — Results of applying control theory to the neural net of worm 11:27 — Control theory for artificial neural networks 12:44 — Comprehensive Python checklist for data scientists.

CompuFlair Website:
www.compu-flair.com.

Chapters:
00:00 — Introduction.
01:52 — Application of control theory in the neural net of worm.
03:23 — Networks in Data Science \& Seven Bridges of Konigsberg Problem.
05:00 — History of network science.
06:22 — Basics of control theory.
10:23 — Results of applying control theory to the neural net of worm.
11:27 — Control theory for artificial neural networks.
12:44 — Comprehensive Python checklist for data scientists.

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